Feature Extraction
Transformers
Safetensors
English
multilingual
laya_browser
laya
custom_code
system-1
browser-agent
web-navigation
decision-model
mmbert
mind2web
tilelang
Instructions to use cklxx/laya-browser with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cklxx/laya-browser with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="cklxx/laya-browser", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("cklxx/laya-browser", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download code/pyproject.toml from cklxx/laya-browser: direct link, hf CLI and curl.
- Browser
- Download file 733 Bytes
-
https://huggingface.co/cklxx/laya-browser/resolve/main/code/pyproject.toml
- Command line
-
hf download hf://cklxx/laya-browser/code/pyproject.toml
-
curl -L -o pyproject.toml https://huggingface.co/cklxx/laya-browser/resolve/main/code/pyproject.toml
733 Bytes
| [project] | |
| name = "laya-browser" | |
| version = "0.1.0" | |
| description = "laya fine-tuned as a browser-agent decision head: server, task suite, fine-tune pipeline" | |
| requires-python = ">=3.11,<3.13" | |
| dependencies = [ | |
| "laya>=0.3.4", | |
| "torch>=2.6", | |
| "transformers>=4.48", | |
| "huggingface_hub>=0.25", | |
| "httpx[http2]>=0.28", | |
| "numpy>=1.24", | |
| ] | |
| [project.optional-dependencies] | |
| fast = ["tilelang>=0.1.14"] # TileLang fast path (code/kernels) | |
| data = ["beautifulsoup4", "lxml", "datasets", "modelscope"] # Mind2Web conversion / dataset eval | |
| browser = ["browser-harness==0.1.13"] # only for the live suite / crawling (jev-ultrafast side) | |
| [tool.uv] | |
| index-url = "https://pypi.tuna.tsinghua.edu.cn/simple" | |